740 lines
31 KiB
YAML
740 lines
31 KiB
YAML
default_max_attempts_per_step: 3
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classifier_model: "MODEL_1"
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feedback_model: "MODEL_1"
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tokens_for_ai_rubric: |
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Evaluate understanding of basic game theory concepts.
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Consider:
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- Grasp of strategic interaction
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- Understanding of Nash equilibrium
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- Recognition of dominant strategies
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- Ability to analyze simple games
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- Application to real-world scenarios
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Provide clear explanations with examples.
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sections:
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- section_id: introduction
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title: Welcome to Game Theory
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steps:
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- step_id: welcome
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title: Strategic Thinking
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content_blocks:
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- "# Game Theory 101: The Science of Strategy 🎮🧠"
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- ""
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- "**Welcome to game theory!**"
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- ""
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- "Game theory is the study of strategic interaction - how people make decisions when their outcomes depend on others' choices."
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- ""
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- "**Not just for games:**"
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- "- Business competition (pricing, market entry)"
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- "- International relations (nuclear deterrence, trade)"
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- "- Biology (evolution, animal behavior)"
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- "- Economics (auctions, bargaining)"
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- "- Everyday life (traffic, cooperation)"
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- ""
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- "**You'll learn:**"
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- "✓ The Prisoner's Dilemma (cooperation vs self-interest)"
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- "✓ Nash Equilibrium (stable strategies)"
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- "✓ Dominant strategies (always-best moves)"
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- "✓ Zero-sum vs positive-sum games"
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- "✓ How to analyze strategic situations"
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- ""
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- "**Real applications:**"
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- "- Why cartels are unstable"
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- "- Why arms races happen"
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- "- When cooperation emerges"
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- "- How auctions should be designed"
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question: Ready to learn how to think strategically about interactive decisions?
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tokens_for_ai: |
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Accept positive responses as 'ready'.
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Language preference as 'set_language'.
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Otherwise 'off_topic'.
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buckets:
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- ready
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- set_language
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- off_topic
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transitions:
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ready:
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content_blocks:
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- "Excellent! Let's start with the most famous game in game theory! 🎯"
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next_section_and_step: prisoners_dilemma:step_1
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set_language:
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content_blocks:
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- "Language preference updated!"
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metadata_add:
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language: "the-users-response"
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counts_as_attempt: false
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next_section_and_step: introduction:welcome
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off_topic:
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content_blocks:
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- "Let's learn strategic thinking together! Ready to begin?"
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counts_as_attempt: false
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next_section_and_step: introduction:welcome
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- section_id: prisoners_dilemma
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title: The Prisoner's Dilemma
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steps:
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- step_id: step_1
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title: The Classic Dilemma
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content_blocks:
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- "## The Prisoner's Dilemma: Cooperation vs Self-Interest 🚔"
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- ""
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- "**The Scenario:**"
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- ""
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- "Two criminals are arrested and interrogated separately. The prosecutor offers each the same deal:"
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- ""
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- "**If you both stay silent:**"
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- "- Each gets 1 year in prison (light sentence, lack of evidence)"
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- ""
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- "**If you betray your partner but they stay silent:**"
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- "- You go free (0 years)"
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- "- Your partner gets 3 years"
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- ""
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- "**If you both betray each other:**"
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- "- Each gets 2 years"
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- ""
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- "**Payoff matrix (years in prison - lower is better):**"
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- ""
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- "```"
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- " Player B"
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- " Silent Betray"
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- "Player A Silent (-1,-1) (-3,0)"
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- " Betray (0,-3) (-2,-2)"
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- "```"
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- ""
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- "**The dilemma:**"
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- "- **Collectively best:** Both stay silent (-1 each)"
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- "- **Individually rational:** Both betray (-2 each)"
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- ""
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- "**Why betray dominates:**"
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- "- If partner stays silent: Betray gets you 0 vs 1 year (betray better!)"
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- "- If partner betrays: Betray gets you 2 vs 3 years (betray better!)"
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- "- No matter what partner does, betraying is better for YOU"
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- ""
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- "**The tragedy:** Both act rationally, both end up worse off (-2 each) than if they'd cooperated (-1 each)!"
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question: "You're playing prisoner's dilemma once with a stranger you'll never meet again. What should you do from a purely self-interested perspective, and why?"
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tokens_for_ai: |
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Correct answer: Betray (or defect/confess)
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Reasoning: Betraying is a DOMINANT STRATEGY
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- Dominates silence regardless of what partner does
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- If partner silent: 0 years better than 1 year
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- If partner betrays: 2 years better than 3 years
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Look for understanding of dominant strategy.
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Categorize as:
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- correct_with_reasoning: Says betray AND explains dominant strategy
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- correct_answer: Says betray without full explanation
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- says_cooperate: Says stay silent (cooperative but not rational in one-shot)
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- game_theory_aware: Mentions dilemma nature even if wrong choice
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- set_language: Language preference
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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If correct:
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- Excellent! Betraying is the DOMINANT STRATEGY.
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- No matter what the other player does, betraying is better for YOU.
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- This is rational but leads to both getting -2 instead of -1.
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- That's the tragedy of the Prisoner's Dilemma!
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If says cooperate:
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- Noble but not strategically optimal in a one-shot game!
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- Betraying DOMINATES: better outcome regardless of partner's choice.
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- In one-shot games with strangers, defection is predicted.
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- (Later we'll see when cooperation can emerge in repeated games!)
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Explain dominant strategy concept clearly.
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buckets:
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- correct_with_reasoning
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- correct_answer
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- says_cooperate
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- game_theory_aware
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- set_language
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- off_topic
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transitions:
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correct_with_reasoning:
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ai_feedback:
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tokens_for_ai: |
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Perfect strategic analysis!
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Betraying is the DOMINANT STRATEGY - always better for you.
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Even though both cooperating would be better collectively (-1 each),
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individual rationality leads to mutual defection (-2 each).
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This is the fundamental insight of game theory!
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metadata_add:
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score: "n+2"
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concepts_mastered: "n+1"
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next_section_and_step: prisoners_dilemma:step_2
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correct_answer:
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ai_feedback:
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tokens_for_ai: |
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Correct! Betraying is the rational choice.
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Why? It's a DOMINANT STRATEGY.
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No matter what your partner does, betraying gives YOU a better outcome.
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If they stay silent: 0 < 1. If they betray: 2 < 3.
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This individual rationality creates the dilemma!
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metadata_add:
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score: "n+1"
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next_section_and_step: prisoners_dilemma:step_2
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says_cooperate:
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ai_feedback:
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tokens_for_ai: |
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Cooperation would be great if you could trust them!
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But from pure self-interest in a ONE-SHOT game:
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Betraying DOMINATES staying silent.
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If they're silent: 0 years (betray) beats 1 year (silent).
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If they betray: 2 years (betray) beats 3 years (silent).
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Betraying is always better for YOU - that's the dilemma!
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next_section_and_step: prisoners_dilemma:step_2
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game_theory_aware:
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ai_feedback:
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tokens_for_ai: |
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You sense the dilemma!
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From pure self-interest: betraying DOMINATES.
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It's better for you no matter what they do.
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Both thinking this way → both defect → both get -2.
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Could've gotten -1 each if they cooperated. That's the tragedy!
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next_section_and_step: prisoners_dilemma:step_2
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set_language:
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content_blocks:
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- "Language updated!"
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metadata_add:
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language: "the-users-response"
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counts_as_attempt: false
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next_section_and_step: prisoners_dilemma:step_1
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off_topic:
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content_blocks:
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- "Think strategically: What gives YOU the best outcome regardless of what your partner does?"
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next_section_and_step: prisoners_dilemma:step_1
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- step_id: step_2
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title: Real-World Dilemmas
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content_blocks:
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- "## Prisoner's Dilemma Everywhere! 🌍"
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- ""
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- "The Prisoner's Dilemma structure appears constantly:"
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- ""
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- "**Business cartels:**"
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- "- Cooperate: Keep prices high (both profit)"
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- "- Defect: Undercut price (steal market share)"
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- "- Problem: Undercutting is always tempting!"
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- "- Result: Cartels are unstable"
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- ""
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- "**Arms races:**"
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- "- Cooperate: Don't build weapons (both save money)"
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- "- Defect: Build weapons (get advantage if opponent doesn't)"
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- "- Problem: Building weapons dominates"
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- "- Result: Costly arms races"
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- ""
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- "**Environmental pollution:**"
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- "- Cooperate: Reduce emissions (collective good)"
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- "- Defect: Pollute freely (save costs)"
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- "- Problem: Individual incentive to pollute"
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- "- Result: Tragedy of the commons"
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- ""
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- "**Doping in sports:**"
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- "- Cooperate: Stay clean (fair competition)"
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- "- Defect: Dope (gain advantage)"
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- "- Problem: If others dope, you must too to compete"
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- "- Result: Widespread doping"
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- ""
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- "**The pattern:**"
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- "Individual rationality → collectively bad outcome"
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question: "Can you think of another real-world situation that has Prisoner's Dilemma structure? Describe what cooperation and defection look like."
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tokens_for_ai: |
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Look for recognition of the PD structure:
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- Two or more parties
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- Temptation to defect while others cooperate
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- Mutual defection worse than mutual cooperation
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- Defection is individually rational
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Examples: cheating in class, tax evasion, littering, free-riding,
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overfishing, etc.
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Categorize as:
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- excellent_example: Clear PD structure with cooperation/defection explained
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- good_example: Recognizes PD structure
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- vague_example: Right idea but unclear
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- not_quite_pd: Example doesn't fit structure
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- set_language: Language preference
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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If they identify a good example:
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- Validate it! Explain how it fits PD structure.
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- Point out: cooperation better collectively, defection individually rational.
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- This recognition helps understand so many social problems!
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If example doesn't quite fit:
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- Acknowledge the thinking.
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- Explain what makes something a PD: mutual defection < mutual cooperation < defection while others cooperate.
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- Offer a clearer example.
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Celebrate their application of game theory!
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buckets:
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- excellent_example
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- good_example
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- vague_example
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- not_quite_pd
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- set_language
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- off_topic
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transitions:
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excellent_example:
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ai_feedback:
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tokens_for_ai: |
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Brilliant example!
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Reference their specific example and confirm the PD structure.
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Point out: cooperation collectively better, but defection individually tempting.
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This is why so many social problems are hard to solve!
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Game theory helps us recognize these structures!
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metadata_add:
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score: "n+2"
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concepts_mastered: "n+1"
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next_section_and_step: nash_equilibrium:step_1
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good_example:
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ai_feedback:
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tokens_for_ai: |
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Great example!
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Confirm it has PD structure: defection tempting, but mutual defection worse.
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This pattern is everywhere once you see it!
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Understanding the structure helps design solutions (regulations, incentives, reputation).
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metadata_add:
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score: "n+1"
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next_section_and_step: nash_equilibrium:step_1
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vague_example:
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ai_feedback:
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tokens_for_ai: |
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Good thinking! Clarify how their example fits:
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Cooperation = ? (collectively better)
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Defection = ? (individually tempting)
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Help them sharpen the structure identification.
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next_section_and_step: nash_equilibrium:step_1
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not_quite_pd:
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ai_feedback:
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tokens_for_ai: |
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Interesting example but not quite Prisoner's Dilemma structure.
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PD needs: mutual cooperation > mutual defection, but defection dominates.
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Their example might be a different game structure.
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Acknowledge their thinking, explain the distinction.
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next_section_and_step: nash_equilibrium:step_1
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set_language:
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content_blocks:
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- "Language updated!"
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metadata_add:
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language: "the-users-response"
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counts_as_attempt: false
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next_section_and_step: prisoners_dilemma:step_2
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off_topic:
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content_blocks:
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- "Think of situations where everyone would be better off cooperating, but individuals are tempted to cheat."
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next_section_and_step: prisoners_dilemma:step_2
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- section_id: nash_equilibrium
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title: Nash Equilibrium
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steps:
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- step_id: step_1
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title: Stable Strategies
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content_blocks:
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- "## Nash Equilibrium: The Stability Concept 🎯"
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- ""
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- "**Named after John Nash (Nobel Prize, 1994)**"
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- ""
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- "**Definition:**"
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- "A Nash Equilibrium is a set of strategies where no player can improve their outcome by unilaterally changing their strategy."
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- ""
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- "**In simpler terms:**"
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- "Everyone is playing their best response to what others are doing. No one wants to deviate."
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- ""
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- "**In Prisoner's Dilemma:**"
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- "Both betraying is a Nash Equilibrium!"
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- "- If A betrays, B's best response is betray (2 < 3 years)"
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- "- If B betrays, A's best response is betray (2 < 3 years)"
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- "- Neither wants to switch to silence unilaterally"
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- ""
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- "**Key insight:**"
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- "Nash Equilibrium ≠ Best outcome for everyone"
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- "It's just stable (self-enforcing)"
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- ""
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- "**Example: Coordination Game**"
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- ""
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- "Two friends picking where to meet:"
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- "```"
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- " Friend B"
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- " Coffee Bar"
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- "Friend A Coffee (2,2) (0,0)"
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- " Bar (0,0) (1,1)"
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- "```"
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- ""
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- "**Two Nash Equilibria:**"
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- "1. Both go to Coffee (2,2)"
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- "2. Both go to Bar (1,1)"
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- ""
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- "Meeting anywhere > missing each other!"
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- "Coordination problems have multiple equilibria."
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question: "In a game where two drivers approach an intersection, each can either Stop or Go. If both Go, they crash (payoff -10 each). If one Stops and one Goes, the goer gets +1 and the stopper gets 0. If both Stop, they're delayed (payoff -1 each). What are the Nash Equilibrium outcomes?"
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tokens_for_ai: |
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Payoff matrix:
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Driver B
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Stop Go
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Driver A Stop (-1,-1) (0,+1)
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Go (+1,0) (-10,-10)
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Nash Equilibria: (Stop, Go) and (Go, Stop)
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- If A stops, B's best response is Go
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- If B goes, A's best response is Stop
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- And vice versa for (Go, Stop)
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NOT Nash Equilibrium:
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- (Stop, Stop): Either could improve by switching to Go
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- (Go, Go): Both would improve by switching to Stop
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Look for identification of the two equilibria.
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Categorize as:
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- correct_both: Identifies both (Stop,Go) and (Go,Stop)
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- identifies_one: Gets one of the two equilibria
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- identifies_pattern: Recognizes one stops, one goes
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- says_both_stop: Says (Stop,Stop) - incorrect
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- confused: Other answers
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- set_language: Language preference
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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Correct equilibria: (Stop, Go) and (Go, Stop)
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If correct:
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- Excellent! Two Nash Equilibria where one stops, one goes.
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- Neither wants to unilaterally change.
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- This is like traffic lights solving coordination!
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If says both stop:
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- That seems safe but it's NOT Nash Equilibrium!
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- If both stop, either could switch to Go and get +1 instead of -1.
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- Nash requires no one wants to unilaterally deviate.
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Explain why the two asymmetric outcomes are stable.
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buckets:
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- correct_both
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- identifies_one
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- identifies_pattern
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- says_both_stop
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- confused
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- set_language
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- off_topic
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transitions:
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correct_both:
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ai_feedback:
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tokens_for_ai: |
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Perfect! Two Nash Equilibria: (Stop,Go) and (Go,Stop).
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In each, no driver wants to unilaterally change.
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Both stopping is NOT equilibrium - either would want to go!
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This coordination problem is solved by traffic lights in reality!
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metadata_add:
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score: "n+2"
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concepts_mastered: "n+1"
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next_section_and_step: dominant_strategies:step_1
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identifies_one:
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ai_feedback:
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tokens_for_ai: |
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Good! You found one equilibrium.
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But there's symmetry - also a Nash Equilibrium where roles reverse!
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Both (Stop,Go) and (Go,Stop) are stable.
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In each, neither wants to unilaterally change.
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metadata_add:
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score: "n+1"
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next_section_and_step: dominant_strategies:step_1
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identifies_pattern:
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ai_feedback:
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tokens_for_ai: |
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Right idea - one stops, one goes!
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Specifically: (Stop,Go) and (Go,Stop) are both Nash Equilibria.
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Neither driver wants to change their strategy given the other's.
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This is a coordination game solved by conventions (like traffic lights!).
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next_section_and_step: dominant_strategies:step_1
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says_both_stop:
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ai_feedback:
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tokens_for_ai: |
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Seems safe, but NOT Nash Equilibrium!
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At (Stop,Stop), either driver could switch to Go:
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Get +1 instead of -1 while other stays stopped.
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Nash requires no one wants to deviate.
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The equilibria are (Stop,Go) and (Go,Stop).
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next_section_and_step: nash_equilibrium:step_1
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confused:
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content_blocks:
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- "Check each outcome: Can any player improve by switching?"
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- "Nash Equilibrium: No player wants to unilaterally change strategy"
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- "Hint: One driver stops, one goes (two ways to do this)"
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next_section_and_step: nash_equilibrium:step_1
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set_language:
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content_blocks:
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- "Language updated!"
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metadata_add:
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language: "the-users-response"
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counts_as_attempt: false
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next_section_and_step: nash_equilibrium:step_1
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off_topic:
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content_blocks:
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- "Find outcomes where neither driver would want to change their choice given what the other is doing."
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next_section_and_step: nash_equilibrium:step_1
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- section_id: dominant_strategies
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title: Dominant Strategies
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steps:
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- step_id: step_1
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title: Always-Best Strategies
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content_blocks:
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- "## Dominant Strategies: No-Brainer Moves 💪"
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- ""
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- "**Definition:**"
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- "A dominant strategy is one that's best regardless of what other players do."
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- ""
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- "**If you have a dominant strategy, PLAY IT!**"
|
|
- ""
|
|
- "**In Prisoner's Dilemma:**"
|
|
- "Betraying is a dominant strategy for both players."
|
|
- "- Better if opponent stays silent: 0 < 1"
|
|
- "- Better if opponent betrays: 2 < 3"
|
|
- "- Always better!"
|
|
- ""
|
|
- "**Dominant Strategy Equilibrium:**"
|
|
- "When all players have dominant strategies, the outcome is certain!"
|
|
- "- Everyone plays their dominant strategy"
|
|
- "- This is always a Nash Equilibrium"
|
|
- "- But Nash Equilibrium doesn't always involve dominant strategies"
|
|
- ""
|
|
- "**Example without dominant strategies:**"
|
|
- ""
|
|
- "Rock-Paper-Scissors:"
|
|
- "- No strategy is always best"
|
|
- "- Best strategy depends on opponent's choice"
|
|
- "- Optimal: Randomize (mixed strategy)"
|
|
- ""
|
|
- "**Why dominant strategies matter:**"
|
|
- "- Simplify analysis (easy to predict)"
|
|
- "- Stable and robust"
|
|
- "- Used in mechanism design (incentive compatibility)"
|
|
question: "A company must choose High Price or Low Price. If both choose High, each earns $100. If both choose Low, each earns $50. If one chooses Low and other High, the low pricer earns $120 and the high pricer earns $20. Does either company have a dominant strategy? If so, what is it?"
|
|
tokens_for_ai: |
|
|
Payoff matrix:
|
|
Company B
|
|
High Low
|
|
Company A High (100,100) (20,120)
|
|
Low (120,20) (50,50)
|
|
|
|
For Company A:
|
|
- If B plays High: Low gives 120 > High gives 100 → Low better
|
|
- If B plays Low: Low gives 50 > High gives 20 → Low better
|
|
- Low DOMINATES High
|
|
|
|
Same logic for Company B.
|
|
Both have dominant strategy: Low Price
|
|
|
|
Look for recognition that Low dominates High.
|
|
|
|
Categorize as:
|
|
- correct_both_low: Says Low is dominant strategy for both
|
|
- says_low: Identifies Low without full explanation
|
|
- says_high: Says High (incorrect - not dominant)
|
|
- says_no_dominant: Says no dominant strategy exists
|
|
- unclear: Confused answer
|
|
- set_language: Language preference
|
|
- off_topic: Unrelated
|
|
feedback_tokens_for_ai: |
|
|
Correct: Low is dominant strategy for BOTH companies.
|
|
|
|
If correct:
|
|
- Excellent! Low dominates High for both.
|
|
- If opponent prices High: 120 > 100 (Low better)
|
|
- If opponent prices Low: 50 > 20 (Low better)
|
|
- Result: Both price low, earn 50 each (could've earned 100 each!)
|
|
- This is another Prisoner's Dilemma structure!
|
|
|
|
If wrong:
|
|
- Check each scenario.
|
|
- Show that Low always outperforms High regardless of opponent.
|
|
- Explain this leads to (Low,Low) equilibrium.
|
|
|
|
Connect to PD structure.
|
|
buckets:
|
|
- correct_both_low
|
|
- says_low
|
|
- says_high
|
|
- says_no_dominant
|
|
- unclear
|
|
- set_language
|
|
- off_topic
|
|
transitions:
|
|
correct_both_low:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
Perfect analysis!
|
|
Low DOMINATES High for both companies.
|
|
No matter what opponent does, Low is better.
|
|
Result: (Low,Low) = $50 each.
|
|
If they could cooperate: (High,High) = $100 each!
|
|
This is Prisoner's Dilemma in business form!
|
|
metadata_add:
|
|
score: "n+2"
|
|
concepts_mastered: "n+1"
|
|
next_section_and_step: conclusion:step_1
|
|
says_low:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
Correct! Low is the dominant strategy.
|
|
Why? Check both scenarios:
|
|
If opponent prices High: 120 (Low) > 100 (High)
|
|
If opponent prices Low: 50 (Low) > 20 (High)
|
|
Always better! This is another PD structure.
|
|
metadata_add:
|
|
score: "n+1"
|
|
next_section_and_step: conclusion:step_1
|
|
says_high:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
High would be great if both could commit!
|
|
But it's NOT dominant. Check:
|
|
If opponent prices Low: 20 (High) < 120 (Low)
|
|
Low is better regardless of opponent.
|
|
This is why cartels are unstable!
|
|
next_section_and_step: dominant_strategies:step_1
|
|
says_no_dominant:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
Actually, there IS a dominant strategy!
|
|
Compare for Company A:
|
|
- If B plays High: Low(120) > High(100)
|
|
- If B plays Low: Low(50) > High(20)
|
|
Low is always better! Same for Company B.
|
|
next_section_and_step: dominant_strategies:step_1
|
|
unclear:
|
|
content_blocks:
|
|
- "For dominant strategy, check: Is one choice ALWAYS better than the other?"
|
|
- "Compare Low vs High when opponent plays High, then when opponent plays Low"
|
|
next_section_and_step: dominant_strategies:step_1
|
|
set_language:
|
|
content_blocks:
|
|
- "Language updated!"
|
|
metadata_add:
|
|
language: "the-users-response"
|
|
counts_as_attempt: false
|
|
next_section_and_step: dominant_strategies:step_1
|
|
off_topic:
|
|
content_blocks:
|
|
- "For each company, which strategy is better regardless of what the opponent does?"
|
|
next_section_and_step: dominant_strategies:step_1
|
|
|
|
- section_id: conclusion
|
|
title: Game Theory Foundations
|
|
steps:
|
|
- step_id: step_1
|
|
title: Strategic Thinking
|
|
content_blocks:
|
|
- "## Congratulations, Game Theorist! 🎓🎮"
|
|
- ""
|
|
- "**You've mastered the fundamentals!**"
|
|
- ""
|
|
- "**What you've learned:**"
|
|
- "✓ Prisoner's Dilemma (cooperation vs self-interest)"
|
|
- "✓ Nash Equilibrium (stable strategy profiles)"
|
|
- "✓ Dominant strategies (always-best moves)"
|
|
- "✓ How to analyze strategic situations"
|
|
- "✓ Why individually rational choices can lead to bad collective outcomes"
|
|
- ""
|
|
- "**Key insights:**"
|
|
- "- Strategic thinking requires considering others' incentives"
|
|
- "- Equilibrium ≠ optimal (Prisoner's Dilemma!)"
|
|
- "- Dominant strategies simplify prediction"
|
|
- "- Coordination problems have multiple equilibria"
|
|
- "- Institutions and repeated play can enable cooperation"
|
|
- ""
|
|
- "**Real-world applications:**"
|
|
- "- Understanding why cartels fail"
|
|
- "- Recognizing arms race dynamics"
|
|
- "- Designing better mechanisms (auctions, voting)"
|
|
- "- Building institutions that align incentives"
|
|
- ""
|
|
- "**Next steps:**"
|
|
- "- Game Theory 201: Mixed strategies and repeated games"
|
|
- "- Look for strategic interactions in daily life"
|
|
- "- Think about how to align individual and collective interests"
|
|
question: "How has learning game theory changed how you think about strategic situations? Give an example where you might apply these concepts."
|
|
tokens_for_ai: |
|
|
This is a reflection question.
|
|
|
|
Look for:
|
|
- Recognition of strategic interdependence
|
|
- Understanding that others' incentives matter
|
|
- Application to real situations
|
|
- Appreciation of conflict between individual/collective rationality
|
|
|
|
Categorize as:
|
|
- excellent_reflection: Insightful application showing deep understanding
|
|
- practical_application: Good real-world example
|
|
- general_reflection: Acknowledges usefulness
|
|
- brief_response: Short but relevant
|
|
- set_language: Language preference
|
|
- off_topic: Unrelated
|
|
feedback_tokens_for_ai: |
|
|
Provide encouraging feedback!
|
|
|
|
Validate their example/reflection.
|
|
Emphasize key takeaway: think about others' incentives!
|
|
Game theory helps predict behavior and design better systems.
|
|
|
|
Mention Game Theory 201 for deeper concepts.
|
|
Celebrate their foundational understanding!
|
|
buckets:
|
|
- excellent_reflection
|
|
- practical_application
|
|
- general_reflection
|
|
- brief_response
|
|
- set_language
|
|
- off_topic
|
|
transitions:
|
|
excellent_reflection:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
Fantastic insight!
|
|
Reference their example specifically.
|
|
You now think strategically about interdependent decisions!
|
|
This foundation enables understanding mechanism design, auctions, bargaining.
|
|
Ready for Game Theory 201 when you are!
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
practical_application:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
Great application!
|
|
Acknowledge their example.
|
|
Game theory is everywhere once you start looking!
|
|
Understanding incentives helps predict and influence behavior.
|
|
Excellent work mastering the fundamentals!
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
general_reflection:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
Good reflection!
|
|
The core lesson: always consider others' incentives.
|
|
Strategic interactions are everywhere - business, politics, daily life.
|
|
You've built a strong foundation in game theory!
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
brief_response:
|
|
ai_feedback:
|
|
tokens_for_ai: |
|
|
Thank you for completing Game Theory 101!
|
|
You've learned to think strategically about interactive decisions.
|
|
These concepts underpin economics, politics, and much more!
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
set_language:
|
|
content_blocks:
|
|
- "Language updated!"
|
|
metadata_add:
|
|
language: "the-users-response"
|
|
counts_as_attempt: false
|
|
next_section_and_step: conclusion:step_1
|
|
off_topic:
|
|
content_blocks:
|
|
- "Reflect: How might understanding incentives and strategic interaction help you in real-world situations?"
|
|
next_section_and_step: conclusion:step_1
|